Unlocking the Power of Amazon Kinesis Video Streams with the Consumer Library for Python

Article

Have you ever wanted to harness the power of video streaming and process the data in real-time? Look no further than the Amazon Kinesis Video Streams Consumer Library for Python. Designed to work seamlessly with Amazon Kinesis Video Streams (KVS), this library allows you to read in streaming bytes from KVS and parse them into individual MKV fragments.

Understanding the Basics

Streaming video data can be a complex task, but with the Amazon Kinesis Video Streams Consumer Library for Python, it becomes much simpler. By making use of the KVS GetMedia or GetMediaForFragmentList API call response, the library efficiently reads the raw bytes and processes them into MKV fragments. These fragments can then be forwarded to callback functions in your application.

What sets this library apart is its ability to parse fragments using EMBLite by MideTechnology. This enables the library to provide both raw byte fragments and a searchable DOM-like structure, enhancing the flexibility and usability of the parsed data.

Key Functions

The KvsFragmentProcessor class, included in the library, offers several essential functions for post-processing of parsed MKV fragments:

1. get_fragment_tags(): Extracts MKV tags from the fragment, allowing for easy categorization and organization of the video content.
2. save_fragment_as_local_mkv(): Saves the fragment as a stand-alone MKV file on the local disk, ensuring easy accessibility and storage.
3. get_frames_as_ndarray(): Returns a selectable ratio of frames in the fragment as a list of NDArray objects, facilitating further analysis and manipulation of the video frames.
4. save_frames_as_jpeg(): Saves a selectable ratio of frames in the fragment as JPEG images on the local disk, suitable for visual inspection and sharing.

Integration and Deployment

Getting started with the Amazon Kinesis Video Streams Consumer Library for Python is straightforward. The provided kvs_consumer_library_example module offers a complete example of how to consume the library. To deploy the example, follow these steps:

1. Ensure you have an active stream running in KVS. The example utilizes fragments from the live edge of the stream. If no fragments are being received, the consumer will gracefully exit. To parse previously stored fragments, update the StartSelector in the kvs_consumer_library_example.
2. Clone the repository and navigate to it using the terminal:
   git clone https://github.com/aws-samples/amazon-kinesis-video-streams-consumer-library-for-python.git
cd amazon-kinesis-video-streams-consumer-library-for-python
3. Install the necessary Python dependencies:
   python3 -m pip install -r requirements.txt
4. Open the cloned repository in your favorite IDE.
5. Update the KVS stream parameters in kvs_consumer_library_example.py, including the REGION and KVS_STREAM01_NAME.
6. Run the example code using the following command:
   python3 kvs_consumer_library_example.py
   It’s important to note that the host machine must have a valid AWS credentials file or receive temporary credentials by other means for successful authentication.

Advantages and Considerations

The Amazon Kinesis Video Streams Consumer Library for Python offers several advantages for developers and enterprises. Its seamless integration with Amazon Kinesis Video Streams allows for real-time video data processing and analysis. By providing parsed MKV fragments and frames, the library simplifies the extraction of valuable insights from streaming video data.

However, it’s essential to consider the timing and async aspects while using the library. Long or external blocking processes in the on_fragment_arrived() callback can introduce additional latency and impact real-time processing. As a developer, threading or developing async solutions can help avoid extended blocking of the consumer library fragment processing.

Looking Ahead

The Amazon Kinesis Video Streams Consumer Library for Python is just the beginning of what’s possible with video streaming and data processing. Its advanced features, such as extracting tags and saving frames as JPEG images, open up exciting opportunities for applications in various domains.

Future updates and developments are underway to enhance the library’s capabilities and improve the user experience. Keep an eye out for added functionalities, performance optimizations, and seamless integrations with other AWS services.

In conclusion, the Amazon Kinesis Video Streams Consumer Library for Python empowers developers and enterprises to unlock the full potential of video streaming data. By simplifying the process of parsing and processing MKV fragments, this library offers an invaluable tool for real-time analysis and insights. Explore the possibilities and embark on your journey towards harnessing the power of video streaming today.